A Molecular View of Dynamic Responses When Mixing Poly(ethylene oxide) and Poly(methyl methacrylate)

Chen, Chunxia; Maranas, Janna K.

doi:10.1021/ma802183h

Cited by 13 publications

(4 citation statements)

References 55 publications

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“…Moreover, the PEO is technically important in many fields. As one consequence, various PEO systems (including melts, solutions, blends, and composites) have been extensively studied using AA MD simulations. In particular, I have previously simulated glass transition behaviors of various PEO systems (bulks, films, and isolated chain), validating the employed force field .…”

Section: Computational Detailsmentioning

confidence: 99%

Multiscale Modeling Scheme for Simulating Polymeric Melts: Application to Poly(Ethylene Oxide)

2017

Macro Theory & Simulations

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polyolefins, from which the volumetric expansive coefficients and glass transition temperatures (T g ) could be determined. Up to now, this method has been extensively applied to complex polymers, [4] including dendrimers [5,6] and crosslinked networks, [7,8] to examine effects of various factors (i.e., molecular weight, [9] tacticity, [10] confinement [11] ) on the volumetric properties.However, in order to achieve repeatable results, adequate thermodynamics equilibrium should be usually attained in these AA MD simulations. Although a great variety of schemes have been proposed to improve the sampling efficiency, restrained by the current computational power, the productive AA MD simulations are only generally suitable for investigating short-term behaviors of small short-chain polymer (namely, oligomer) systems. To study specific polymer systems at the wide timeand space-scales, one of quite promising schemes is multiscale modeling, which groups every AA segment into one super-atom or coarse-grained (CG) bead. [12,13] In this scheme, it is critical to obtain the "potential energy" (referred to free energy or potential of mean force in most cases) that can accurately describe chain structure and interbead interactions. [14,15] Numerous CG methods have been developed, [16] among which most typical ones include iterative Boltzmann inversion (IBI), [17] force match, [18][19][20] inverse Monte Carlo, [21] conditional reversible work (CRW), [22,23] and MARTINI, [24] etc. Mainly, these methods differ in the target functions that are used to parameterize the nonbonded CG potentials. For example, the IBI method [17] adopts the structural distributions, the CRW method [22] uses the interaction free energy, and the MARTINI method [24] aims to reproduce the partitioning free energies.In general, the CG potentials parameterized until now suffer from representability and transferability. [16,25,26] Namely, even at the same state as the parameterized one with some properties, simulations with these CG potentials cannot reproduce other properties; and CG potentials that are parameterized at some state cannot reliably be used at other states. In order to improve the predictive power of CG simulations, numerous studies have been carried out during the past decade. Here only some of typical ones are mentioned. As one of early works, Qian et al. [27] modified the IBI potentials by a temperature factor to reproduce the thermal expansion coefficients over a broad range of temperature. This method was called one-point extrapolation Multiscale SimulationsThe poly(ethylene oxide) (PEO) is employed as one typical example to demonstrate a new multiscale modeling scheme for simulating high-molecularweight polymeric melts. In this scheme, the structural distributions and the densities at five elevated temperatures at 1 atm, which are obtained from molecular dynamics (MD) simulations of all-atomistic oligomeric melt, are employed as the target functions to parameterize the coarse-grained (CG) potentials. The extensive CG MD simulations rep...

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Section: Computational Detailsmentioning

confidence: 99%

Multiscale Modeling Scheme for Simulating Polymeric Melts: Application to Poly(Ethylene Oxide)

2017

Macro Theory & Simulations

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“…In the last several years, the preparation and studies established that the blending of PMMA and PEO is an effective and economic way of creating high performance material to overcome the drawbacks of the individual polymer . The blending of a small amount of PEO in the PMMA matrix results in a large increase of PMMA flexibility and reduces its brittleness, and simultaneously the PMMA environment increases the amorphous phase of semicrystalline PEO.…”

Section: Introductionmentioning

confidence: 99%

Structural and dielectric studies of amorphous and semicrystalline polymers blend‐based nanocomposite electrolytes

Choudhary

Sengwa

2014

J of Applied Polymer Sci

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The solid polymeric nanocomposite electrolyte (SPNE) films based on the blend of amorphous poly(methyl methacrylate) (PMMA) and semicrystalline poly(ethylene oxide) (PEO) (PMMA:PEO 5 80:20 wt %) doped with lithium perchlorate (LiClO 4 ) salt and montmorillonite (MMT) clay nanofiller were prepared by classical solution cast, ultrasonic assisted solution cast and ultrasonication along with microwave irradiated solution cast followed by melt-pressing methods. The X-ray diffraction study of these electrolytes revealed the amorphous behavior with intercalated MMT structures. The suppressed crystallinity of PEO in the blend electrolyte complexes confirmed the existence of single discrete PEO chains confined within the PMMA domains. The dielectric relaxation spectroscopy of these materials was performed over the frequency range 20 Hz to 1 MHz, at ambient temperature. The presence of a singular relaxation peak in the loss tangent and electric modulus spectra of these electrolytes confirms a coupled cooperative chain segmental dynamics of the blend polymer owing to their miscible amorphous morphology. The behavior of transient complexes formed between the polymers functional groups, lithium cations and the intercalated MMT nanoplatelets was explored. The ambient temperature ionic conductivity of these electrolytes depends on the structural dynamics and the sample preparation methods. It is revealed that the presence of PEO in the PMMA matrix mainly governs the structural, dielectric, and ionic properties of these SPNE films.

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“…This is the case of binary mixtures of poly(ethylene oxide) (PEO) ( T g PEO ≈ 220 K) and poly(methyl methacrylate) (PMMA) ( T g PMMA ≈ 400 K). In fact, these blends have attracted great attention in the scientific community. − Because of crystallization at moderate contents of PEO, most investigations have focused on compositions rich in the PMMA component (about 80% in PMMA). We note that in such cases the glass transition feature accessed e.g.…”

Section: Introductionmentioning

confidence: 99%

Investigation of a Nanocomposite of 75 wt % Poly(methyl methacrylate) Nanoparticles with 25 wt % Poly(ethylene oxide) Linear Chains: A Quasielatic Neutron Scattering, Calorimetric, and WAXS Study

et al. 2014

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We have investigated the thermal behavior, local structure, and dynamics in a system where 25 wt % PEO [poly(ethylene oxide)] linear chains are mixed with 75 wt % PMMA [poly(methyl methacrylate)] soft nanoparticles. Calorimetric and wide-angle X-ray scattering experiments point to a weak penetration of the PEO chains in the nanoparticles, qualifying the mixture as a nanocomposite. Quasi-elastic neutron scattering (QENS) experiments on partially deuterated samples has selectively revealed the component dynamics in the system. The α-methyl group dynamics of PMMA, which fall within the QENS time scale in the temperature range investigated, are hardly affected by the presence of PEO except for hints of a more heterogeneous environment in the nanocomposite than in bulk PMMA. The effects on the dynamics of PEO are more interesting. The observation of dynamics in the microseconds range for the PEO component of the nanocomposite at temperatures at which the calorimetric experiments indicate the freezing of its segmental relaxation provides evidence for confined dynamics below the main glass transition of the mixtureattributable to the effective glass transition of the slow component. A parallel study on an equivalent blend of PEO and linear PMMA chains shows that these effects are independent of the topology of the PMMA. However, well above the effective glass transition of the slow component, the dynamics of PEO differ in both systems. In the linear blend, PEO segments move with the typical features of supercooled polymers in metastable equilibrium, while in the nanocomposite PEO dynamics exhibit an anomalously strong deviation from Gaussian behavior. This deviation grows with increased mobility of the nanoparticles. PEO segments are seemingly trapped in effective cages imposed by the nanoparticles for a very long timemore than 2 orders of magnitude longer than in bulk or when surrounded by linear PMMA chainsbefore the subdiffusive process leading to segmental relaxation sets in. We speculate that local loops in the surface of the nanoparticles may play an important role in this trapping mechanism.

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A Molecular View of Dynamic Responses When Mixing Poly(ethylene oxide) and Poly(methyl methacrylate)

Cited by 13 publications

References 55 publications

Multiscale Modeling Scheme for Simulating Polymeric Melts: Application to Poly(Ethylene Oxide)

Multiscale Modeling Scheme for Simulating Polymeric Melts: Application to Poly(Ethylene Oxide)

Structural and dielectric studies of amorphous and semicrystalline polymers blend‐based nanocomposite electrolytes

Investigation of a Nanocomposite of 75 wt % Poly(methyl methacrylate) Nanoparticles with 25 wt % Poly(ethylene oxide) Linear Chains: A Quasielatic Neutron Scattering, Calorimetric, and WAXS Study

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